利用机器人顾问对财务规划管理信息系统进行战略设计

Y. Saputra, Ela Siti Nurpajriah, Siti Kustinah, N. Putri
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引用次数: 0

摘要

现代信息技术的发展速度如此之快,以至于金融欺诈现已蔓延到可再生技术领域。保证未来财务安全的唯一方法就是投资。然而,包括股票、黄金和其他投资在内的大量投资选择往往让人们难以做出最佳决定。 许多千禧一代仍然对投资心存疑虑。 这是因为他们对有效投资缺乏了解。 为了提高社会和千禧一代对投资的兴趣,有必要使用机器学习信息系统来帮助人们选择投资产品。该系统的构建采用了马科维茨算法和 K-近邻算法。K 近邻算法是一种机器学习技术,可以帮助找到与风险状况相匹配的投资组合建议。 根据对系统计算和人工计算得出的锐利比率的比较,确定了马科维茨和 KNN 方法的准确率水平,即 99.15%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Perancangan Strategis Sistem Informasi Financial Planning Management dengan Robo-Advisor
The pace of information technology growth in the modern day is so rapid that financial fraud has now spread to renewable technologies. The only approach to guarantee future financial security is to invest. However, the vast array of investment options—including stocks, gold, and other investments—often makes it difficult for people to make the best decision.  Many millennials are still apprehensive about investing.  This results from a lack of understanding about effective investing.  A machine learning information system is necessary to assist in the selection of investment products in order to boost the community's and millennials' interest in investing. The Markowitz and K-Nearest Neighbor algorithms were used in the system's construction. Finding recommendations for investment portfolios that match the risk profile can be aided using the K-Nearest Neighbor approach, which is a machine learning technique.  Based on a comparison of the sharpe ratio findings from system calculations and manual calculations, the accuracy level of the Markowitz and KNN approaches, which was set at 99.15%, was established.
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